Principal Associate Data Scientist, Machine Learning

Capital One Capital One · Banking · Toronto, ON

This role focuses on building, deploying, and maintaining machine learning models, including Gradient Boosting Machines and Neural Networks, within a financial services context. The data scientist will also develop and optimize model development pipelines, design experiments, and investigate new technologies. Experience with Python, SQL, version control, and ML frameworks is required, with preferred qualifications including cloud platforms, advanced Git, CI/CD, experimental design, and AI agent usage.

What you'd actually do

  1. Building, deploying, and maintaining machine learning models (Gradient Boosting Machines, Neural Networks, etc.) from development, validation, through to deployment in production
  2. Developing and optimization model development pipelines that enable rapid experimentation and optimization
  3. Writing software to extract, clean, and investigate large, messy data sets of numerical and textual data
  4. Designing and analyzing experiments to optimize business strategies
  5. Investigating the impact of new technologies, data sources, and methodologies in order to remain on the cutting edge of data science.

Skills

Required

  • Python
  • R
  • GitHub
  • SQL
  • machine learning
  • predictive modeling

Nice to have

  • AWS
  • experimental design
  • AI agent power user
  • financial data

What the JD emphasized

  • cutting edge models
  • model development
  • model deployment
  • inference

Other signals

  • building cutting edge models
  • deploying and maintaining machine learning models
  • model development pipelines
  • optimize business strategies
  • AI agent power user